Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning

Robin L. Miller-Coleman, Jeremy A. Dodsworth, Christian A. Ross, Everett L. Shock, Amanda J. Williams, Hilairy E. Hartnett, Austin I. McDonald, Jeff R Havig, Brian P. Hedlund

    Research output: Contribution to journalArticle

    22 Citations (Scopus)

    Abstract

    Over 100 hot spring sediment samples were collected from 28 sites in 12 areas/regions, while recording as many coincident geochemical properties as feasible (>60 analytes). PCR was used to screen samples for Korarchaeota 16S rRNA genes. Over 500 Korarchaeota 16S rRNA genes were screened by RFLP analysis and 90 were sequenced, resulting in identification of novel Korarchaeota phylotypes and exclusive geographical variants. Korarchaeota diversity was low, as in other terrestrial geothermal systems, suggesting a marine origin for Korarchaeota with subsequent niche-invasion into terrestrial systems. Korarchaeota endemism is consistent with endemism of other terrestrial thermophiles and supports the existence of dispersal barriers. Korarchaeota were found predominantly in >55°C springs at pH 4.7-8.5 at concentrations up to 6.6×106 16S rRNA gene copies g-1 wet sediment. In Yellowstone National Park (YNP), Korarchaeota were most abundant in springs with a pH range of 5.7 to 7.0. High sulfate concentrations suggest these fluids are influenced by contributions from hydrothermal vapors that may be neutralized to some extent by mixing with water from deep geothermal sources or meteoric water. In the Great Basin (GB), Korarchaeota were most abundant at spring sources of pH<7.2 with high particulate C content and high alkalinity, which are likely to be buffered by the carbonic acid system. It is therefore likely that at least two different geological mechanisms in YNP and GB springs create the neutral to mildly acidic pH that is optimal for Korarchaeota. A classification support vector machine (C-SVM) trained on single analytes, two analyte combinations, or vectors from non-metric multidimensional scaling models was able to predict springs as Korarchaeota-optimal or sub-optimal habitats with accuracies up to 95%. To our knowledge, this is the most extensive analysis of the geochemical habitat of any high-level microbial taxon and the first application of a C-SVM to microbial ecology.

    Original languageEnglish (US)
    Article numbere35964
    JournalPloS one
    Volume7
    Issue number5
    DOIs
    StatePublished - May 4 2012

    Fingerprint

    Korarchaeota
    Hot springs
    Hot Springs
    hot springs
    artificial intelligence
    Learning systems
    niches
    biogeography
    Genes
    basins
    Support vector machines
    Sediments
    Carbonic Acid
    ribosomal RNA
    Water
    Ecology
    Alkalinity
    national parks
    thermophilic microorganisms
    indigenous species

    Cite this

    Miller-Coleman, R. L., Dodsworth, J. A., Ross, C. A., Shock, E. L., Williams, A. J., Hartnett, H. E., ... Hedlund, B. P. (2012). Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning. PloS one, 7(5), [e35964]. https://doi.org/10.1371/journal.pone.0035964

    Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning. / Miller-Coleman, Robin L.; Dodsworth, Jeremy A.; Ross, Christian A.; Shock, Everett L.; Williams, Amanda J.; Hartnett, Hilairy E.; McDonald, Austin I.; Havig, Jeff R; Hedlund, Brian P.

    In: PloS one, Vol. 7, No. 5, e35964, 04.05.2012.

    Research output: Contribution to journalArticle

    Miller-Coleman, RL, Dodsworth, JA, Ross, CA, Shock, EL, Williams, AJ, Hartnett, HE, McDonald, AI, Havig, JR & Hedlund, BP 2012, 'Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning', PloS one, vol. 7, no. 5, e35964. https://doi.org/10.1371/journal.pone.0035964
    Miller-Coleman, Robin L. ; Dodsworth, Jeremy A. ; Ross, Christian A. ; Shock, Everett L. ; Williams, Amanda J. ; Hartnett, Hilairy E. ; McDonald, Austin I. ; Havig, Jeff R ; Hedlund, Brian P. / Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning. In: PloS one. 2012 ; Vol. 7, No. 5.
    @article{57ac1d9e624b4f7f964f347ca8a281ec,
    title = "Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning",
    abstract = "Over 100 hot spring sediment samples were collected from 28 sites in 12 areas/regions, while recording as many coincident geochemical properties as feasible (>60 analytes). PCR was used to screen samples for Korarchaeota 16S rRNA genes. Over 500 Korarchaeota 16S rRNA genes were screened by RFLP analysis and 90 were sequenced, resulting in identification of novel Korarchaeota phylotypes and exclusive geographical variants. Korarchaeota diversity was low, as in other terrestrial geothermal systems, suggesting a marine origin for Korarchaeota with subsequent niche-invasion into terrestrial systems. Korarchaeota endemism is consistent with endemism of other terrestrial thermophiles and supports the existence of dispersal barriers. Korarchaeota were found predominantly in >55°C springs at pH 4.7-8.5 at concentrations up to 6.6×106 16S rRNA gene copies g-1 wet sediment. In Yellowstone National Park (YNP), Korarchaeota were most abundant in springs with a pH range of 5.7 to 7.0. High sulfate concentrations suggest these fluids are influenced by contributions from hydrothermal vapors that may be neutralized to some extent by mixing with water from deep geothermal sources or meteoric water. In the Great Basin (GB), Korarchaeota were most abundant at spring sources of pH<7.2 with high particulate C content and high alkalinity, which are likely to be buffered by the carbonic acid system. It is therefore likely that at least two different geological mechanisms in YNP and GB springs create the neutral to mildly acidic pH that is optimal for Korarchaeota. A classification support vector machine (C-SVM) trained on single analytes, two analyte combinations, or vectors from non-metric multidimensional scaling models was able to predict springs as Korarchaeota-optimal or sub-optimal habitats with accuracies up to 95{\%}. To our knowledge, this is the most extensive analysis of the geochemical habitat of any high-level microbial taxon and the first application of a C-SVM to microbial ecology.",
    author = "Miller-Coleman, {Robin L.} and Dodsworth, {Jeremy A.} and Ross, {Christian A.} and Shock, {Everett L.} and Williams, {Amanda J.} and Hartnett, {Hilairy E.} and McDonald, {Austin I.} and Havig, {Jeff R} and Hedlund, {Brian P.}",
    year = "2012",
    month = "5",
    day = "4",
    doi = "10.1371/journal.pone.0035964",
    language = "English (US)",
    volume = "7",
    journal = "PLoS One",
    issn = "1932-6203",
    publisher = "Public Library of Science",
    number = "5",

    }

    TY - JOUR

    T1 - Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning

    AU - Miller-Coleman, Robin L.

    AU - Dodsworth, Jeremy A.

    AU - Ross, Christian A.

    AU - Shock, Everett L.

    AU - Williams, Amanda J.

    AU - Hartnett, Hilairy E.

    AU - McDonald, Austin I.

    AU - Havig, Jeff R

    AU - Hedlund, Brian P.

    PY - 2012/5/4

    Y1 - 2012/5/4

    N2 - Over 100 hot spring sediment samples were collected from 28 sites in 12 areas/regions, while recording as many coincident geochemical properties as feasible (>60 analytes). PCR was used to screen samples for Korarchaeota 16S rRNA genes. Over 500 Korarchaeota 16S rRNA genes were screened by RFLP analysis and 90 were sequenced, resulting in identification of novel Korarchaeota phylotypes and exclusive geographical variants. Korarchaeota diversity was low, as in other terrestrial geothermal systems, suggesting a marine origin for Korarchaeota with subsequent niche-invasion into terrestrial systems. Korarchaeota endemism is consistent with endemism of other terrestrial thermophiles and supports the existence of dispersal barriers. Korarchaeota were found predominantly in >55°C springs at pH 4.7-8.5 at concentrations up to 6.6×106 16S rRNA gene copies g-1 wet sediment. In Yellowstone National Park (YNP), Korarchaeota were most abundant in springs with a pH range of 5.7 to 7.0. High sulfate concentrations suggest these fluids are influenced by contributions from hydrothermal vapors that may be neutralized to some extent by mixing with water from deep geothermal sources or meteoric water. In the Great Basin (GB), Korarchaeota were most abundant at spring sources of pH<7.2 with high particulate C content and high alkalinity, which are likely to be buffered by the carbonic acid system. It is therefore likely that at least two different geological mechanisms in YNP and GB springs create the neutral to mildly acidic pH that is optimal for Korarchaeota. A classification support vector machine (C-SVM) trained on single analytes, two analyte combinations, or vectors from non-metric multidimensional scaling models was able to predict springs as Korarchaeota-optimal or sub-optimal habitats with accuracies up to 95%. To our knowledge, this is the most extensive analysis of the geochemical habitat of any high-level microbial taxon and the first application of a C-SVM to microbial ecology.

    AB - Over 100 hot spring sediment samples were collected from 28 sites in 12 areas/regions, while recording as many coincident geochemical properties as feasible (>60 analytes). PCR was used to screen samples for Korarchaeota 16S rRNA genes. Over 500 Korarchaeota 16S rRNA genes were screened by RFLP analysis and 90 were sequenced, resulting in identification of novel Korarchaeota phylotypes and exclusive geographical variants. Korarchaeota diversity was low, as in other terrestrial geothermal systems, suggesting a marine origin for Korarchaeota with subsequent niche-invasion into terrestrial systems. Korarchaeota endemism is consistent with endemism of other terrestrial thermophiles and supports the existence of dispersal barriers. Korarchaeota were found predominantly in >55°C springs at pH 4.7-8.5 at concentrations up to 6.6×106 16S rRNA gene copies g-1 wet sediment. In Yellowstone National Park (YNP), Korarchaeota were most abundant in springs with a pH range of 5.7 to 7.0. High sulfate concentrations suggest these fluids are influenced by contributions from hydrothermal vapors that may be neutralized to some extent by mixing with water from deep geothermal sources or meteoric water. In the Great Basin (GB), Korarchaeota were most abundant at spring sources of pH<7.2 with high particulate C content and high alkalinity, which are likely to be buffered by the carbonic acid system. It is therefore likely that at least two different geological mechanisms in YNP and GB springs create the neutral to mildly acidic pH that is optimal for Korarchaeota. A classification support vector machine (C-SVM) trained on single analytes, two analyte combinations, or vectors from non-metric multidimensional scaling models was able to predict springs as Korarchaeota-optimal or sub-optimal habitats with accuracies up to 95%. To our knowledge, this is the most extensive analysis of the geochemical habitat of any high-level microbial taxon and the first application of a C-SVM to microbial ecology.

    UR - http://www.scopus.com/inward/record.url?scp=84860507088&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84860507088&partnerID=8YFLogxK

    U2 - 10.1371/journal.pone.0035964

    DO - 10.1371/journal.pone.0035964

    M3 - Article

    C2 - 22574130

    AN - SCOPUS:84860507088

    VL - 7

    JO - PLoS One

    JF - PLoS One

    SN - 1932-6203

    IS - 5

    M1 - e35964

    ER -